|
|
Absolute deviation, 绝对离差
* h# c. C( s8 T: V+ b( e7 q+ {Absolute number, 绝对数3 s8 [7 \1 [+ M. E5 b' i/ [. _. V% m
Absolute residuals, 绝对残差
/ [/ }2 @0 X! PAcceleration array, 加速度立体阵
- x# v; S- F n7 R( x8 tAcceleration in an arbitrary direction, 任意方向上的加速度
6 Z9 L; D# S6 ~, Q0 Z/ _2 fAcceleration normal, 法向加速度
; e: b$ w& p* K2 E( m4 J. BAcceleration space dimension, 加速度空间的维数) R- x& ?7 ] c% [$ \) U. R
Acceleration tangential, 切向加速度
. e0 t/ U+ }9 g$ }Acceleration vector, 加速度向量
! h& v' e8 F0 d% _% iAcceptable hypothesis, 可接受假设- f% P# p3 G* G4 l' h
Accumulation, 累积% z, {" O1 B8 W8 d
Accuracy, 准确度2 E1 w/ Y) c2 P1 y
Actual frequency, 实际频数
& S; z" W& E! y0 U4 ]4 HAdaptive estimator, 自适应估计量9 o7 _6 f! C) j3 H7 O1 K& U
Addition, 相加! }% K/ X4 A) N( E2 _
Addition theorem, 加法定理6 H3 v7 }; a2 ~7 s& |
Additivity, 可加性( f# i0 H( v g
Adjusted rate, 调整率; _9 K" i( U$ Y6 f4 Z& J7 U
Adjusted value, 校正值
, u* d Z+ ~4 W; | UAdmissible error, 容许误差
. H# \! a' u; A7 H) PAggregation, 聚集性; k! A" }7 s5 }' v# ]! B" p9 u: [+ M
Alternative hypothesis, 备择假设1 h" W }0 v% G! i
Among groups, 组间
' k% y2 h9 `$ }3 X4 w6 sAmounts, 总量
& C9 k6 T- f. a) z% \Analysis of correlation, 相关分析
' }& m1 V( }" [1 t6 [5 G. \6 U# BAnalysis of covariance, 协方差分析
2 m J2 A9 Z7 f1 s4 v5 p" sAnalysis of regression, 回归分析 D' h. u. {/ c }
Analysis of time series, 时间序列分析1 K- I# {8 m6 M0 P! y
Analysis of variance, 方差分析
+ O9 h9 H( z. D. |$ q3 Z9 } O% x( B3 kAngular transformation, 角转换
5 k6 v" j/ p1 R, y' E sANOVA （analysis of variance）, 方差分析8 B. c ?1 F, j" k$ x2 D& S
ANOVA Models, 方差分析模型6 Y% d: c8 }% h* F) j+ z
Arcing, 弧/弧旋 U* T- V1 b: M9 w9 u9 C0 O
Arcsine transformation, 反正弦变换
# L c& i# e$ zArea under the curve, 曲线面积
, p2 @; q; S; G) O! x9 Y- \9 w/ F1 LAREG , 评估从一个时间点到下一个时间点回归相关时的误差
1 @4 d; C/ ~" G* n$ rARIMA, 季节和非季节性单变量模型的极大似然估计 8 C& E* t% s1 P. h* E1 [
Arithmetic grid paper, 算术格纸' O" b1 A8 A5 n1 w& l0 h
Arithmetic mean, 算术平均数7 f/ f, c# b# }. G
Arrhenius relation, 艾恩尼斯关系' }7 s7 |6 [ ]$ o- P
Assessing fit, 拟合的评估6 B& K! a4 u# \+ I
Associative laws, 结合律0 {$ l0 p; |% e) U8 t6 I: Q2 F: ^
Asymmetric distribution, 非对称分布
7 B# F, E8 x [9 O! XAsymptotic bias, 渐近偏倚
& v9 E1 B9 y; SAsymptotic efficiency, 渐近效率* R1 c; P7 E- E$ I
Asymptotic variance, 渐近方差! ]1 ?- @+ \; d# ?. k
Attributable risk, 归因危险度: n4 j& P% a3 I) L, J
Attribute data, 属性资料+ v) M6 v2 u( y
Attribution, 属性: b/ _/ v/ l a
Autocorrelation, 自相关
2 E1 I4 c2 q1 L" l6 JAutocorrelation of residuals, 残差的自相关
/ j. U% n: Q+ i% w1 v+ lAverage, 平均数
) o3 K; ^& j' D! \' NAverage confidence interval length, 平均置信区间长度- x# V2 A& E8 E# U4 j% r
Average growth rate, 平均增长率+ f, s4 O- w6 x* q0 @
Bar chart, 条形图9 N6 F, a ?# [( }* T0 Q" f/ m
Bar graph, 条形图
V2 w1 f2 [ `Base period, 基期 B; ^% n9 y' a: R- B% `' b3 d
Bayes' theorem , Bayes定理+ h0 ^: K; ?: V% [
Bell-shaped curve, 钟形曲线9 f* A$ O$ J( F7 |+ J* S0 j+ g
Bernoulli distribution, 伯努力分布3 ]# A! ?" g! Y" o& H
Best-trim estimator, 最好切尾估计量
; ?( _5 r8 ^1 J, {, qBias, 偏性
( j* Y6 B& @ D ^2 M9 qBinary logistic regression, 二元逻辑斯蒂回归
! q6 T& N0 c! c2 tBinomial distribution, 二项分布
2 G- d2 ], }( p9 fBisquare, 双平方9 J7 W5 X5 F/ L3 v6 U
Bivariate Correlate, 二变量相关
+ [. A6 N% C+ T8 r8 T$ j& BBivariate normal distribution, 双变量正态分布
$ l5 E7 k2 T% V6 t5 ?Bivariate normal population, 双变量正态总体& \: d5 O' ^" G/ o8 W& A* }
Biweight interval, 双权区间
! S3 G- ]& G) {; @Biweight M-estimator, 双权M估计量# f# G! k( g5 B: `; |1 b. Q
Block, 区组/配伍组
$ l5 t t% V& B& l! y3 ZBMDP(Biomedical computer programs), BMDP统计软件包
% \8 V+ m* j" yBoxplots, 箱线图/箱尾图/ T. u1 Q7 c# o; X; z
Breakdown bound, 崩溃界/崩溃点
# R( ?1 J( o: t! i3 p; w. VCanonical correlation, 典型相关1 x4 e& X. @% o7 h4 ?$ k/ T
Caption, 纵标目/ f1 t% H( \/ @* ]- V4 I
Case-control study, 病例对照研究
: D7 e; y l5 ^( j- n# ICategorical variable, 分类变量
+ J% L" |4 N1 u! m4 }Catenary, 悬链线
2 h @/ K( I* I1 |8 F( a/ Z" SCauchy distribution, 柯西分布2 x: C4 Q1 F ]
Cause-and-effect relationship, 因果关系
; u/ e& ^4 s( b( O8 vCell, 单元. v4 ~* n* f/ U' h/ @" h/ v9 `
Censoring, 终检/ ]3 n, ~6 E' i
Center of symmetry, 对称中心! F1 j" i- R, S" D. \; Q$ {! j
Centering and scaling, 中心化和定标; n: v0 e2 D/ L7 f; p: ~+ j. c- a
Central tendency, 集中趋势3 w# D9 o' O7 T( N6 f) i0 @
Central value, 中心值( m1 V6 p. p% ]/ G4 |: Q$ s& A
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测7 ~; j# t1 ?1 G3 T! V3 ]5 `' Z @9 _
Chance, 机遇
& f) `( L W+ yChance error, 随机误差
: R2 K: d$ M$ j- YChance variable, 随机变量4 N6 v4 e- z9 j7 _, X9 Z
Characteristic equation, 特征方程
# u& S( @( |2 E2 n, x; yCharacteristic root, 特征根% \! c# l3 n8 Z) n
Characteristic vector, 特征向量
" j; X- `; Z4 XChebshev criterion of fit, 拟合的切比雪夫准则3 P/ }1 P# j# |% B
Chernoff faces, 切尔诺夫脸谱图
7 N3 ?0 a! }+ b6 Q/ U' Y FChi-square test, 卡方检验/χ2检验
4 s: ~! f" p. s+ b) P. J, KCholeskey decomposition, 乔洛斯基分解9 d# T! Q' r1 U' g& R( c. o3 x. u- B
Circle chart, 圆图
0 [+ D5 [! p' L5 g! xClass interval, 组距
+ [" ]* q/ [' a/ Y* eClass mid-value, 组中值; a7 }- W+ A& q! F2 Q) ?
Class upper limit, 组上限$ b2 _& z7 @6 \/ r; o
Classified variable, 分类变量
: ~6 a; h6 f* x, }& f2 |Cluster analysis, 聚类分析
' x. j. G; a8 c: D" gCluster sampling, 整群抽样' D7 K- Y! z6 }, U" |4 _% F* O. P
Code, 代码
7 O' m1 I$ p2 i2 p9 D+ V( ]Coded data, 编码数据3 _* W" i8 ~; }, W' k2 U% w# \
Coding, 编码$ I- d0 v; }* X) J8 b) p5 q
Coefficient of contingency, 列联系数
6 |5 y9 T0 f. z) ?3 A/ oCoefficient of determination, 决定系数
9 L" m5 y& t0 o5 S2 M8 xCoefficient of multiple correlation, 多重相关系数
2 U0 l" g9 ~ i0 \; c$ XCoefficient of partial correlation, 偏相关系数
! q# h1 v7 }9 J e3 n$ \0 KCoefficient of production-moment correlation, 积差相关系数
" J9 X- D* T7 ~$ o+ D$ D! kCoefficient of rank correlation, 等级相关系数. }4 I, ^5 T1 [
Coefficient of regression, 回归系数
+ I, b! y1 _0 tCoefficient of skewness, 偏度系数
$ @& C6 f- b7 f b$ }- ^3 ^Coefficient of variation, 变异系数
; A) j& R* b1 K5 O# }9 kCohort study, 队列研究 X+ ^4 ^8 n! [! C
Column, 列8 R6 j: U3 l! B2 u' O9 t: \
Column effect, 列效应
& n- A8 a7 g# Y% p5 x3 XColumn factor, 列因素( S8 Q9 c: h+ B, ~$ X
Combination pool, 合并4 ] W$ M0 E9 I L1 `; }; {, q
Combinative table, 组合表9 y5 |: Q) Z' c, H, G) j2 ?" x4 a6 n
Common factor, 共性因子
) ^- b3 ]" V* {Common regression coefficient, 公共回归系数$ g3 N" r; i' c
Common value, 共同值
8 W9 Y. S9 C: [) i* E9 {( uCommon variance, 公共方差6 d" K3 T7 _. `. l; b- S) X$ d
Common variation, 公共变异
1 N9 ^4 @: U& E; a+ _% tCommunality variance, 共性方差+ a. S7 d- J& j) G6 a# e- v6 f
Comparability, 可比性
; K- Y' A8 u' U- \+ e( \4 YComparison of bathes, 批比较4 k7 O' Y( T5 u. ^
Comparison value, 比较值6 l9 L8 l: ^' v* O; m8 g
Compartment model, 分部模型" S; }6 q; U" P) d, Z, A% F T
Compassion, 伸缩5 N& [" H6 ^3 o3 g
Complement of an event, 补事件
! e1 z' _. Y- N9 `9 `, LComplete association, 完全正相关
# l+ z; s' F. bComplete dissociation, 完全不相关
4 h, _+ d# Q; M2 S( U* m; x& Y; eComplete statistics, 完备统计量* [4 {/ V( q, [
Completely randomized design, 完全随机化设计# X" B+ w8 j% f- J9 j6 V
Composite event, 联合事件
2 a; p# c" x6 d* xComposite events, 复合事件 Z$ X- i* L$ {1 S3 E2 O
Concavity, 凹性2 s$ M! i H: E6 ]5 k2 U& `4 z
Conditional expectation, 条件期望( t/ v! V0 b6 p+ ^$ Q4 j6 P
Conditional likelihood, 条件似然
$ P1 ]" |3 q7 q. vConditional probability, 条件概率
* j# c3 d5 ~/ T! [$ tConditionally linear, 依条件线性2 n# Z( Q" _$ x
Confidence interval, 置信区间
$ X* X$ p* q8 F) oConfidence limit, 置信限% S& g1 H5 c3 c' j9 M6 C# Y* \4 K
Confidence lower limit, 置信下限; p1 g& R% d/ `1 T
Confidence upper limit, 置信上限
6 T1 I# i ]0 Z8 G+ a5 JConfirmatory Factor Analysis , 验证性因子分析
- _/ I" |) J$ k4 w$ xConfirmatory research, 证实性实验研究( R, C- k: T- V! o% h) t' V
Confounding factor, 混杂因素2 p- u( I) x! M, K$ j3 K u0 y8 d
Conjoint, 联合分析
$ z" `5 @& y0 b. Y! jConsistency, 相合性1 D- m) {: K3 }4 s
Consistency check, 一致性检验+ A4 S4 i4 t$ f9 ?
Consistent asymptotically normal estimate, 相合渐近正态估计3 h# C" J1 D2 K8 C- {: U8 \
Consistent estimate, 相合估计
" x. G/ f3 j( R+ w! r. |8 MConstrained nonlinear regression, 受约束非线性回归+ D( }8 h3 h- I- N
Constraint, 约束
) A9 {" \) u" ?+ x! NContaminated distribution, 污染分布
9 U A5 X2 D/ W' [" e' o" KContaminated Gausssian, 污染高斯分布) z; X- {. Z# P! A3 r* P g; a; i
Contaminated normal distribution, 污染正态分布. ^: @' ~- e N0 k0 g4 V- B
Contamination, 污染
$ E# x9 ? E2 Y$ PContamination model, 污染模型
$ k6 c J2 O; D3 e' S# H- aContingency table, 列联表) b# X6 O' ~' F. Q# t, \* I
Contour, 边界线
: x; R$ \( V& \) F- }: wContribution rate, 贡献率/ W& {9 p, O3 T5 E5 n3 ?( W
Control, 对照% {8 `6 [$ `% l7 |( [# f' l# f# ^9 r
Controlled experiments, 对照实验4 {& I& K1 B/ i& }
Conventional depth, 常规深度. [- q; U/ m- f+ ^$ k4 v/ J
Convolution, 卷积* E$ w* {+ J6 [1 y( u" P0 v
Corrected factor, 校正因子3 [% N9 P1 h) N1 O* M/ G
Corrected mean, 校正均值2 ]9 ]3 v2 C# f0 s; s h1 R
Correction coefficient, 校正系数
* F2 d. {+ T: G: pCorrectness, 正确性
- f& U# j5 z0 x/ R$ ?, Z FCorrelation coefficient, 相关系数 ] R' v) G. ^0 f3 L
Correlation index, 相关指数
0 |3 M K$ Z4 m9 m4 O* E, UCorrespondence, 对应3 o8 S+ o# y& O- E7 O
Counting, 计数
' ]0 s3 c' O8 Q( ^Counts, 计数/频数
; \5 o7 b5 \) D6 f k! @8 xCovariance, 协方差% |0 g( d$ S4 s) \) h! C1 D- M% q* ]
Covariant, 共变
) R. l( g- H# Y# E8 YCox Regression, Cox回归
7 v4 e: j% J+ W* ACriteria for fitting, 拟合准则: Z6 ^, Q* w" a6 ~
Criteria of least squares, 最小二乘准则
U) y. m+ n2 KCritical ratio, 临界比
1 ?/ `0 r l( {) l( l- A7 ]Critical region, 拒绝域# V6 _0 y# I8 V3 V0 D' ^' H
Critical value, 临界值 \$ U& m: M7 N2 U6 Y$ G5 F
Cross-over design, 交叉设计
b. ^- x" t! s1 YCross-section analysis, 横断面分析
3 t) @. ]' O6 d R( YCross-section survey, 横断面调查. R7 Z7 \) @* D& f P( l
Crosstabs , 交叉表 + C: d/ \$ v3 x' `. A5 V$ H( m9 R
Cross-tabulation table, 复合表8 I( ^+ q, C: l2 `1 `2 _- U
Cube root, 立方根
7 E# \: ^- ~, K6 v3 v7 tCumulative distribution function, 分布函数
- ]5 N: i9 | k2 i3 A& LCumulative probability, 累计概率9 w( Z- R' I$ [3 y" L. w% w
Curvature, 曲率/弯曲
/ B; E8 b. N6 g" S; q* Y; VCurvature, 曲率
" J. G( M+ ~" i# C( u4 bCurve fit , 曲线拟和 5 y& Z: C; n6 @! a# O8 I9 @
Curve fitting, 曲线拟合+ v7 z' K. ?6 ~1 g; F% \8 f
Curvilinear regression, 曲线回归9 j# d. w8 j! z4 ]% G
Curvilinear relation, 曲线关系& V+ U1 k2 I# E5 A2 L
Cut-and-try method, 尝试法
! p# a# _: A# X# [9 KCycle, 周期
K3 v: r) q! M0 f5 ~, W MCyclist, 周期性
y0 J6 K& |# j2 aD test, D检验
% D" e2 q# Q: e1 [* z g1 w$ oData acquisition, 资料收集4 f, a' u0 z9 _2 V
Data bank, 数据库2 _$ w0 M7 c! A" }* m
Data capacity, 数据容量/ R% e3 T. j8 f& u
Data deficiencies, 数据缺乏. _- ?& [# |$ f, ]2 {! F2 J8 ?
Data handling, 数据处理
& V. ~+ @7 c. a9 S7 f. ~. D9 aData manipulation, 数据处理
2 I5 j8 d( S) }% FData processing, 数据处理
6 f& h6 [; P' M8 C7 q! Q8 {; vData reduction, 数据缩减& Q5 g6 z6 f5 d% O$ N# O6 U
Data set, 数据集- U2 M0 S: c( Y2 q" n8 Y9 ?# Q. I
Data sources, 数据来源
: i% y5 u( n* OData transformation, 数据变换
5 R4 P, I4 @5 r! j2 u3 z' `4 XData validity, 数据有效性+ }6 \9 X' ?5 M& k6 T& F& } F' E0 c
Data-in, 数据输入
, J3 m& t: N8 CData-out, 数据输出
/ p8 l {* C3 {" r% xDead time, 停滞期, |% E; O. S* R9 U% s/ V
Degree of freedom, 自由度* [& `, ^$ v6 d9 m9 O: Z, N
Degree of precision, 精密度
/ o. D5 v8 r. [" w. UDegree of reliability, 可靠性程度0 t5 I" d3 c% u1 w
Degression, 递减
. e( d* E* m u' `( M: n" xDensity function, 密度函数9 B4 g/ k# ~4 k7 n
Density of data points, 数据点的密度
# @; n6 G3 u1 c8 M, cDependent variable, 应变量/依变量/因变量
$ l0 s& h( M+ b) c0 v) k2 t- ?Dependent variable, 因变量
! @6 }: l4 a% j/ V( \, b2 QDepth, 深度$ {/ S' F0 [( {. V) v, B a5 I i
Derivative matrix, 导数矩阵 P c3 P, K' u- G2 y: m
Derivative-free methods, 无导数方法, X, D) w2 U* u8 l9 w/ a* ^
Design, 设计9 ~1 a4 x0 x; E* a. v ^
Determinacy, 确定性& E# t: S# J+ e T2 ?
Determinant, 行列式
$ T t' _! f) @) D9 DDeterminant, 决定因素6 c1 s! [% E% p) c* ?( ]: ]2 g
Deviation, 离差
5 P5 q0 s" @; ODeviation from average, 离均差
' T, \6 Z/ w' w4 z# JDiagnostic plot, 诊断图
3 ~6 p* D/ h4 I" f& S6 i9 u" ADichotomous variable, 二分变量
+ ^; U5 L& S2 {. EDifferential equation, 微分方程1 a' W! \( r9 f
Direct standardization, 直接标准化法
, y, t# p9 x* h* NDiscrete variable, 离散型变量. \% r1 e! P" B' w& |
DISCRIMINANT, 判断 5 Q/ w4 N1 r/ e Z& z% b B# z1 \
Discriminant analysis, 判别分析
: ?+ {5 S1 H" h }. |: i1 iDiscriminant coefficient, 判别系数# [5 i! S6 ~4 T$ |0 I& y5 [% U
Discriminant function, 判别值; N$ T& O* Z# l. N2 R- P: S
Dispersion, 散布/分散度
% _ k% a6 P# v0 D$ C4 JDisproportional, 不成比例的) y/ A* L$ v1 m* }( q: K
Disproportionate sub-class numbers, 不成比例次级组含量
. A0 m3 }! h* d% X) R- i' x4 m* ]Distribution free, 分布无关性/免分布! S5 G* S2 B( \8 b
Distribution shape, 分布形状8 v3 j7 J6 M8 W4 G7 K: w
Distribution-free method, 任意分布法7 m- G' l, V5 ^, X
Distributive laws, 分配律
2 l7 g6 o7 _5 N- Q0 B8 W" Y1 KDisturbance, 随机扰动项+ C5 ^4 w) v) s* k5 P7 J5 A
Dose response curve, 剂量反应曲线
' p9 i& z; e8 yDouble blind method, 双盲法* q( a/ [) Y4 t! Y) A
Double blind trial, 双盲试验* V7 t8 M0 a c& {) \9 b8 ^- j5 o- {
Double exponential distribution, 双指数分布
9 u0 {+ k8 L5 _# {$ w+ {( s5 O1 x7 RDouble logarithmic, 双对数
1 [9 ~2 c3 p Z, T' z; aDownward rank, 降秩
9 l, X1 `. j$ V' f' {: c6 j8 M6 G0 HDual-space plot, 对偶空间图
/ y* o1 ?: b5 v1 x5 t% _* kDUD, 无导数方法
, ~; v& k% @* _- z2 j. tDuncan's new multiple range method, 新复极差法/Duncan新法
" E9 }8 I/ q, ^( hEffect, 实验效应
& P4 t' J. o v" n8 j+ kEigenvalue, 特征值8 V; b9 _' a) v- p! |
Eigenvector, 特征向量' j4 C, }! T. ^
Ellipse, 椭圆
4 n/ y' w% l' r. b; @" H# G4 kEmpirical distribution, 经验分布
! a% v, A0 R. [7 A; B" d/ KEmpirical probability, 经验概率单位/ z; ]. O# H( Q4 O6 \( W% e
Enumeration data, 计数资料
2 m3 y3 Z, P% S( [: p7 z0 SEqual sun-class number, 相等次级组含量
# V0 y1 U+ H1 w/ n Z4 W' l: z7 u7 KEqually likely, 等可能) E8 x; k$ w- L) _2 q$ I
Equivariance, 同变性
! t( F8 k/ r$ _" r7 D" |4 W" qError, 误差/错误$ z9 d# I& l/ N
Error of estimate, 估计误差
$ O X, f7 l8 Q9 m) u8 z( R1 S1 j3 GError type I, 第一类错误
8 r0 w+ \) I: LError type II, 第二类错误7 h p( ?* a( ]$ e2 [3 u/ v
Estimand, 被估量
! `1 D! g9 r* Z8 ~( ` MEstimated error mean squares, 估计误差均方
# r2 e+ L6 O e, n1 O$ CEstimated error sum of squares, 估计误差平方和
# ^3 X X7 ^8 q' F4 X# ?; p, ~Euclidean distance, 欧式距离
/ F4 ~3 v# \' e- L9 E" [Event, 事件
7 s7 V' k# p) S6 j, R% u; [9 uEvent, 事件6 _5 A/ P0 k' C5 t0 X
Exceptional data point, 异常数据点9 N* |6 f1 N$ w/ T8 T+ T# {
Expectation plane, 期望平面' L0 l( A7 X2 y8 U% p# w/ ^0 E, L
Expectation surface, 期望曲面
5 S% U' ]4 D7 K: ~2 ~, iExpected values, 期望值# `' @7 C6 j% I& F: H$ }$ V+ t
Experiment, 实验
1 R# D1 X3 ]$ r% I3 Y" J7 S HExperimental sampling, 试验抽样% i. t# }. |0 w' P4 X' ^5 z( R# j
Experimental unit, 试验单位. S3 N; r; ]0 T* W
Explanatory variable, 说明变量, a6 y" h2 I. [, Q
Exploratory data analysis, 探索性数据分析
c' E+ l6 ~; \5 S& MExplore Summarize, 探索-摘要( F0 }6 x- `" a5 Q
Exponential curve, 指数曲线
" }* k \# Z# M+ XExponential growth, 指数式增长
) l$ h( @* O- z5 c. ?! dEXSMOOTH, 指数平滑方法 * y) N0 S: |! z; `2 N8 a
Extended fit, 扩充拟合
- I0 l) k$ c" `3 WExtra parameter, 附加参数2 d5 ]* K1 j# c* |5 g+ k) o" z0 I
Extrapolation, 外推法
1 f& W. u0 O- R6 D2 w1 ~1 HExtreme observation, 末端观测值4 U; R$ l* v* {$ N+ [- M1 J4 U. X
Extremes, 极端值/极值
- @7 r b3 L* _* jF distribution, F分布
, S/ u: @8 H( e/ @ E# Z" r) ~ rF test, F检验
& `2 K* y! n" a& tFactor, 因素/因子
- h$ l' `7 ~( Y6 Q9 TFactor analysis, 因子分析
' \* h' k3 @- d0 LFactor Analysis, 因子分析" @! o( v- H s
Factor score, 因子得分 . M, g) V! ]" [7 {7 {! U E* C( ?
Factorial, 阶乘3 n, V$ {" B, \5 F4 l9 a0 J1 r3 o2 C
Factorial design, 析因试验设计
; ]* s) @; f9 R' T4 y1 P- v" c4 `False negative, 假阴性
- l/ D1 s0 w. G, O+ fFalse negative error, 假阴性错误
8 Z9 m U ~9 y+ n/ UFamily of distributions, 分布族
& S5 c' t6 ?1 w, ~Family of estimators, 估计量族
; v5 E" V6 w& m% V/ wFanning, 扇面
& d; k2 ~ j" bFatality rate, 病死率6 U ] N5 X5 l. d& z
Field investigation, 现场调查
8 \/ G! b1 c6 z p. C) {Field survey, 现场调查
3 C1 `+ F& k8 v# @Finite population, 有限总体& W P* }. g( M# b: M: B# D' Y
Finite-sample, 有限样本
4 P* s% V8 }, X; u! D+ c! [/ dFirst derivative, 一阶导数
5 I1 D" ~7 d/ F4 I1 J! p; Q1 PFirst principal component, 第一主成分
% R' }1 g( S, {. s) j3 L6 Q! {5 UFirst quartile, 第一四分位数
* z2 E+ m+ h5 f% A; P1 Z# \Fisher information, 费雪信息量; K& T2 H3 p( x2 k/ D, N j
Fitted value, 拟合值8 f: E3 C# E6 c9 v/ q8 I1 a( A
Fitting a curve, 曲线拟合( M, ]* b1 G' Q" m9 E1 _$ ?- {
Fixed base, 定基
) Q- ~( k. j6 G; DFluctuation, 随机起伏
/ f& h0 c2 x g( T" n8 x8 F& ZForecast, 预测3 y# b. b8 s! I
Four fold table, 四格表: Q/ k" B. }( K" \+ N8 p
Fourth, 四分点7 D. ~7 O* K3 g7 s0 c
Fraction blow, 左侧比率- P U/ E x, x; N K, [
Fractional error, 相对误差
2 X) ` K" v. \) K" m1 z% UFrequency, 频率
: l. P" R, }$ Q0 x& u' sFrequency polygon, 频数多边图" r" G, s$ E! T6 t9 T2 j/ @" U# ^8 O
Frontier point, 界限点* C) D+ N8 x' Q; b: e
Function relationship, 泛函关系- z- U+ h3 D0 z/ F1 r, T
Gamma distribution, 伽玛分布
" n Z# j* K" J+ N3 y( yGauss increment, 高斯增量+ [2 c: i% g2 M' g! i( \
Gaussian distribution, 高斯分布/正态分布
F. `' G4 j$ v9 |, ^Gauss-Newton increment, 高斯-牛顿增量
- y8 Y' s: i1 o# n$ F: _2 z' [9 kGeneral census, 全面普查9 p/ H4 m h- c; y/ E7 J, h
GENLOG (Generalized liner models), 广义线性模型 - p) [, _8 q: u+ j, m
Geometric mean, 几何平均数
1 y6 F* X1 |: M, A& u9 B6 a* oGini's mean difference, 基尼均差
) e5 x a% u7 @$ G1 S4 h9 a7 RGLM (General liner models), 一般线性模型 - V! b" h/ s" v+ Q, W' r+ ^
Goodness of fit, 拟和优度/配合度: a, }% i9 ~" T5 z' k4 h. @
Gradient of determinant, 行列式的梯度$ l' `: o0 f5 v
Graeco-Latin square, 希腊拉丁方: o6 t* O: T- q5 t4 |: u& O
Grand mean, 总均值: |' K$ m( f. |3 g' H! O
Gross errors, 重大错误
! G7 R$ ` h. t2 t$ M' X/ _4 PGross-error sensitivity, 大错敏感度
2 o3 c) \! @0 t/ ?0 C: VGroup averages, 分组平均
. ] k! S! f- F1 i0 W& x# WGrouped data, 分组资料# M0 Y5 f5 Q0 j: M1 P9 N. l
Guessed mean, 假定平均数. z! x; {" k- o ~; Z2 g1 d
Half-life, 半衰期4 |6 a5 B! N& Y# l V) G5 c
Hampel M-estimators, 汉佩尔M估计量
+ k& K4 ?( t; q0 PHappenstance, 偶然事件
/ @9 @5 u( P2 oHarmonic mean, 调和均数7 k$ V3 w* g7 Q* I8 }$ J, o
Hazard function, 风险均数
7 _$ v/ R E1 e" p. c$ J: _Hazard rate, 风险率6 \) F2 z- @3 U- d4 Y: y6 W
Heading, 标目 }! k: e; O/ A3 q% ~# j2 `% j) c
Heavy-tailed distribution, 重尾分布
" X2 w3 v: R) o) r s a, R8 ?Hessian array, 海森立体阵+ N* k* \: T( v% e$ ~+ `
Heterogeneity, 不同质+ [2 w! ?3 J8 H; Q4 r% M& R4 j
Heterogeneity of variance, 方差不齐
& R7 t& w6 ~$ t9 t8 a. |Hierarchical classification, 组内分组
$ ?! H9 P4 s1 r) z; P1 eHierarchical clustering method, 系统聚类法
5 F5 B# g3 x/ g0 n; b: h) V! R+ o, vHigh-leverage point, 高杠杆率点
$ n& P, p; j) O$ l, r. C3 F) DHILOGLINEAR, 多维列联表的层次对数线性模型# J6 p! { J* l5 B' c- m+ S- z
Hinge, 折叶点( B" _+ U% [, Q! M8 l+ Z7 x2 A h
Histogram, 直方图- I) K3 R; |* r4 ^( H
Historical cohort study, 历史性队列研究 ! B2 n% f5 Q1 \0 \, N; r
Holes, 空洞
7 l. F4 O9 @3 l6 S, hHOMALS, 多重响应分析
/ p4 F! }* D6 V- q3 I! xHomogeneity of variance, 方差齐性$ O" |5 j* i6 P1 p, `
Homogeneity test, 齐性检验4 K% x2 v& e4 S: n) z V1 F0 R7 l
Huber M-estimators, 休伯M估计量
9 D& m$ ?& U# R0 c0 d4 L+ ZHyperbola, 双曲线7 u) A+ v4 T4 \- i4 u w E
Hypothesis testing, 假设检验4 k2 J$ t, U! X* F
Hypothetical universe, 假设总体; o# N. E# t7 A% G7 [/ `" n" N
Impossible event, 不可能事件# S, E# O5 c) t9 Q5 n3 T
Independence, 独立性
9 c+ M3 X4 D. w1 LIndependent variable, 自变量9 w( c6 I: j; x8 e! y4 u
Index, 指标/指数
& e7 ~; A6 L- ^7 {Indirect standardization, 间接标准化法
! U% M4 B# C7 sIndividual, 个体
9 P* c) L# }$ z' FInference band, 推断带
& a! @7 \% t$ o* ?Infinite population, 无限总体* p& ~/ m( O- q" U) E$ t) m4 S M
Infinitely great, 无穷大
: X% c; @7 G1 x' U- W) ~) h/ \/ zInfinitely small, 无穷小
6 b1 {, }( f$ I7 @! N& B9 gInfluence curve, 影响曲线
& J" g" \. m5 vInformation capacity, 信息容量- Z9 [! W* S$ H9 z/ q* J' I
Initial condition, 初始条件, F$ }3 V# V- n1 t6 A m! \: N( k
Initial estimate, 初始估计值
9 j% x( }! E* Q. \: w1 `3 y& ?Initial level, 最初水平
2 h; `# W; K+ ?+ AInteraction, 交互作用6 ~) ^8 q, b. k' t
Interaction terms, 交互作用项1 f3 M: R, U3 e: T4 L9 Q& Y
Intercept, 截距2 h% z6 p, f7 S; a. \' X7 P
Interpolation, 内插法, q3 L/ X, Y$ M
Interquartile range, 四分位距
. M* M) z' j5 w$ l: OInterval estimation, 区间估计
+ A3 i' a4 [- L/ I! F! ?' |Intervals of equal probability, 等概率区间) `' [) G( X- a6 @! m, x J- J9 o
Intrinsic curvature, 固有曲率4 m4 w! n; R( ` a" P3 W
Invariance, 不变性
6 P, |% e6 l4 jInverse matrix, 逆矩阵
/ X$ R9 Z7 Q: }4 R' TInverse probability, 逆概率
3 U5 X8 ~. O, l3 j1 OInverse sine transformation, 反正弦变换
`! B8 L3 g h* \& gIteration, 迭代
# O' i/ } n) @9 w0 {Jacobian determinant, 雅可比行列式' ^6 [ |: m; D9 k+ D3 ]) s, f2 K. E% V
Joint distribution function, 分布函数
- }) \$ o$ M/ t+ F6 v5 J dJoint probability, 联合概率) g1 w% T( j2 V; a2 [# ^, G$ d
Joint probability distribution, 联合概率分布
; U" }$ p7 D* X+ ~ v) ZK means method, 逐步聚类法1 ^2 B! X5 n+ f ]& C& v# s
Kaplan-Meier, 评估事件的时间长度
/ \( p8 Z2 {( o: u7 t5 p( P/ pKaplan-Merier chart, Kaplan-Merier图* m2 M3 K. K b8 F/ M
Kendall's rank correlation, Kendall等级相关
3 a( n1 [: J7 L6 F/ m+ B+ D" ZKinetic, 动力学
% [/ [6 Z9 S5 }' JKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
% V- |: `/ e4 W& d, N6 c, G' a' F$ IKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验% b3 l' r4 x$ l% s( f( n% e
Kurtosis, 峰度- t0 w: `) x$ T% E3 Z$ ]
Lack of fit, 失拟4 f7 V( f- _$ q
Ladder of powers, 幂阶梯
! Z0 J+ i s7 f1 sLag, 滞后
9 s2 f/ j- s2 `2 N6 |0 Q, ?Large sample, 大样本" {% a `4 I) S' _! U
Large sample test, 大样本检验$ D" `. F6 A; \
Latin square, 拉丁方. [; W+ ~! k7 H: ~6 \2 `. P
Latin square design, 拉丁方设计
; P% W$ m3 r$ m5 f5 `4 cLeakage, 泄漏
- v+ Y( ^5 ?% p j8 A! ~3 @Least favorable configuration, 最不利构形( U" n j8 P. G& w' d; c% R; \
Least favorable distribution, 最不利分布
, p4 ~1 |# @8 c# s9 U" {- CLeast significant difference, 最小显著差法
; w# W7 m% {3 y. Q5 ALeast square method, 最小二乘法$ w: P5 c) B. @( n/ @: v- P* X) ^$ z
Least-absolute-residuals estimates, 最小绝对残差估计
* l8 K0 |$ `4 i) p+ a4 D$ o- s* HLeast-absolute-residuals fit, 最小绝对残差拟合
+ |4 E& g! S( u) n- kLeast-absolute-residuals line, 最小绝对残差线
' D& w2 T, Z& l: a! U/ uLegend, 图例
2 O! w9 C6 @. J6 RL-estimator, L估计量2 B1 T* H& \+ U `( e6 H- x) G
L-estimator of location, 位置L估计量
- Q/ {* D' f3 Q& z, C& ~! XL-estimator of scale, 尺度L估计量
/ w) e0 S3 G! z9 \Level, 水平
% S% e. m, q" P* O/ z; ~Life expectance, 预期期望寿命: U1 Z$ D8 c+ d- l
Life table, 寿命表, I5 y8 Y' ?1 u6 J0 b6 O( e+ E
Life table method, 生命表法
+ v0 l7 \3 J6 T% e- B% B1 B( e) V. xLight-tailed distribution, 轻尾分布
6 o' I* c5 Z* Q8 _! l0 ]4 vLikelihood function, 似然函数& m! y* k% A, t5 V+ \
Likelihood ratio, 似然比
# O0 K! m, @* ?5 u0 Vline graph, 线图
; A5 E7 O0 m f# {2 ILinear correlation, 直线相关
1 B: J0 [) ~. CLinear equation, 线性方程- r# H; L9 r+ v m
Linear programming, 线性规划
" |2 C4 [# s1 _Linear regression, 直线回归
2 [) J0 n T& ~8 Z1 [% P2 y6 aLinear Regression, 线性回归# m( u$ Q2 [8 Y* I" V' v
Linear trend, 线性趋势8 r' I1 J7 n# s( N
Loading, 载荷 # T/ {& ~$ a+ ~3 C7 P( D) G' C
Location and scale equivariance, 位置尺度同变性0 D: l+ _' o/ b, T7 I$ k) X) d/ A
Location equivariance, 位置同变性! K/ P; A5 @, ]9 o8 ~. R- ~
Location invariance, 位置不变性) X4 h5 q! l6 A2 V- R0 a
Location scale family, 位置尺度族" K9 s" k7 {. ]" s) r' h' _) Y" F
Log rank test, 时序检验 ; M+ V- x" V" Y! D' e6 |/ J* x" v
Logarithmic curve, 对数曲线 E7 |& O. B- { \7 ?0 W9 H
Logarithmic normal distribution, 对数正态分布
# r+ Y, a/ ]) r& G) PLogarithmic scale, 对数尺度+ t5 t. O/ L. |+ U$ m) N
Logarithmic transformation, 对数变换( \/ z4 f: R+ F* T
Logic check, 逻辑检查2 [' u- f+ v7 B. ^
Logistic distribution, 逻辑斯特分布4 c0 `6 I3 c- z; O, c" T% s
Logit transformation, Logit转换! D/ W# ^0 e5 l& S
LOGLINEAR, 多维列联表通用模型
0 @- |- Z+ p: v9 |" \, VLognormal distribution, 对数正态分布& d0 i& F4 n/ H3 P! L
Lost function, 损失函数4 d- [/ b# U4 u% t0 {, x
Low correlation, 低度相关
6 A0 m8 `5 l m" ]8 kLower limit, 下限' o1 M6 R0 z2 s- X5 G. X
Lowest-attained variance, 最小可达方差1 w0 _0 _$ z* U4 u. N' J; C
LSD, 最小显著差法的简称# q( z: V" G& } f' L1 N4 ~7 E
Lurking variable, 潜在变量
$ G2 W8 c, j- k Q' }* `; [Main effect, 主效应
" ~& G1 r, g) S, L. B& xMajor heading, 主辞标目
`3 J- [0 @3 T( d1 A+ M7 {% CMarginal density function, 边缘密度函数7 g) [0 q$ [& w6 u* j O! u
Marginal probability, 边缘概率
: f" S: i% J0 BMarginal probability distribution, 边缘概率分布
3 a! A4 m& i- t7 x+ p0 c% oMatched data, 配对资料" i9 V7 ]& W7 T4 Z9 w O8 o, i
Matched distribution, 匹配过分布
4 R7 P. Q' ^2 wMatching of distribution, 分布的匹配
% X% y' N3 ?/ YMatching of transformation, 变换的匹配, f( t& f3 m9 e; U# \6 \4 ]+ K' p- ^1 `
Mathematical expectation, 数学期望$ E; H& O8 y4 @! }
Mathematical model, 数学模型- j3 ~# s7 ?" v
Maximum L-estimator, 极大极小L 估计量! Y/ P8 {+ P' l% i i. s5 |/ V
Maximum likelihood method, 最大似然法
4 J' T6 d0 @7 }' R; `Mean, 均数, m1 S4 `/ N" P8 B4 Q+ u* E5 R& z
Mean squares between groups, 组间均方# d! ?* ?" y; W5 [( _, _3 c$ p
Mean squares within group, 组内均方0 P H# O- i H* a6 W
Means (Compare means), 均值-均值比较- s7 U( `! X% y6 Z% d' h3 H
Median, 中位数; x' w2 Y% b1 X. z% d5 g
Median effective dose, 半数效量1 ~6 u0 C/ F5 A( c; n' ]) l
Median lethal dose, 半数致死量0 D% V6 N2 B9 @' l; m( R
Median polish, 中位数平滑
( t0 ], J" ~9 H" t& Y T! cMedian test, 中位数检验
7 V: e2 c( h$ C, G& c. F- w- IMinimal sufficient statistic, 最小充分统计量
! @7 u/ ~4 ? U# o9 V! F8 fMinimum distance estimation, 最小距离估计
* H1 K( V* K/ [2 SMinimum effective dose, 最小有效量
( w$ x) a2 z( z; b: r4 M2 }- qMinimum lethal dose, 最小致死量7 m S+ W) r# G: T8 a
Minimum variance estimator, 最小方差估计量
* a4 v; M7 G0 F5 s' e2 rMINITAB, 统计软件包
# I. y& m$ {! rMinor heading, 宾词标目+ W& z: `- m+ {; h
Missing data, 缺失值
& h" a- k7 n, C4 r' |" x( yModel specification, 模型的确定+ C& w6 D) o7 d0 u
Modeling Statistics , 模型统计
( _; G+ c7 U2 `- A$ |Models for outliers, 离群值模型
' Q( |) A$ c9 o! jModifying the model, 模型的修正7 m k3 ~* Y r4 P/ n* J/ {, C
Modulus of continuity, 连续性模
- ^: }4 p0 f" ?. E( W" gMorbidity, 发病率 ) q! h! E1 V' H4 g E0 L
Most favorable configuration, 最有利构形
1 }- V, j7 n, ~% p! Q1 dMultidimensional Scaling (ASCAL), 多维尺度/多维标度$ d6 Z0 e0 A% f1 F
Multinomial Logistic Regression , 多项逻辑斯蒂回归% B& q; ?1 | a& E4 y3 ]9 X2 d1 k) Y
Multiple comparison, 多重比较6 w6 G @2 Q2 i- e
Multiple correlation , 复相关
]# z7 Y M+ RMultiple covariance, 多元协方差( M3 G. Z7 n, n: M* V
Multiple linear regression, 多元线性回归
( A+ s* v: y& z0 y" UMultiple response , 多重选项
3 W) x' L1 r4 l, D) Q( RMultiple solutions, 多解. j8 |- _& \6 t& |6 ^$ h: `
Multiplication theorem, 乘法定理% V* ]4 ^8 T/ J, O7 q& a0 a
Multiresponse, 多元响应
7 _- A4 O4 e$ H, w& @2 MMulti-stage sampling, 多阶段抽样& H; k9 R$ h6 A$ f; ^
Multivariate T distribution, 多元T分布8 G4 y0 f; v% k* V0 e
Mutual exclusive, 互不相容# O0 \0 R" j" F7 b, r* V$ k. H
Mutual independence, 互相独立0 G6 B) H; G. ?* f0 h
Natural boundary, 自然边界) l; X4 v* ~9 j# m. D4 P( e7 B( B
Natural dead, 自然死亡( W+ M, v( A7 `( R1 {: U0 C3 Q
Natural zero, 自然零8 ~* w, @$ O. q
Negative correlation, 负相关
- a; T7 Y3 o) j7 g% j& uNegative linear correlation, 负线性相关6 @; _: ?5 o& s( F+ S: }7 G
Negatively skewed, 负偏: D! Z0 c# f& g! M! Y" M$ R5 }6 O9 e
Newman-Keuls method, q检验
* u( }' F% x3 Q" d* V% `. WNK method, q检验. {% T( H/ [! ^- J3 G: }8 d
No statistical significance, 无统计意义
+ h% s9 H" I* H6 HNominal variable, 名义变量2 r# o9 F3 Y: X4 A9 B
Nonconstancy of variability, 变异的非定常性- J& h6 w7 ^' r& X* b6 V
Nonlinear regression, 非线性相关- n0 E3 p2 u3 y0 a* @4 ^9 B
Nonparametric statistics, 非参数统计0 J# V8 Y& B8 p; M+ T. J
Nonparametric test, 非参数检验
7 s6 e- [. P7 I% N% E5 {3 g' U1 hNonparametric tests, 非参数检验
4 O+ N+ n0 N1 }- Y8 ^Normal deviate, 正态离差
5 c( Z# g* Q @! `( y* [; h qNormal distribution, 正态分布
( {/ B+ J5 R8 @Normal equation, 正规方程组
9 \! w3 ]2 Z, R; ^, jNormal ranges, 正常范围
" y" v6 h; U. NNormal value, 正常值
$ x0 D# a- l) ~, o3 N$ eNuisance parameter, 多余参数/讨厌参数0 D2 [9 u$ x- k5 p. A. s. ~5 K
Null hypothesis, 无效假设 0 `# n' i6 ~9 u/ _* s, U- \
Numerical variable, 数值变量9 f9 T2 t3 ]% P4 N2 i
Objective function, 目标函数6 w' D1 k$ o) A4 s" e# `
Observation unit, 观察单位
/ r" F/ h# e2 d$ r) GObserved value, 观察值- f- T6 K3 i" ^4 G
One sided test, 单侧检验
! s& H8 ]# M9 b/ j/ u; Q( W) N: sOne-way analysis of variance, 单因素方差分析( o' P$ C/ p8 b2 ^2 x1 Y
Oneway ANOVA , 单因素方差分析. T. e: }/ P4 Z+ S$ G$ m
Open sequential trial, 开放型序贯设计
: g3 K: ^! L I6 W* z) y7 mOptrim, 优切尾
. j3 a3 X0 J* x5 |; B, w9 @Optrim efficiency, 优切尾效率
/ A! i( ~) h) a/ t! E# X9 lOrder statistics, 顺序统计量
O1 d8 `0 i0 ?8 {" _8 p0 KOrdered categories, 有序分类7 i* O# y3 f2 b/ a6 i$ u- f
Ordinal logistic regression , 序数逻辑斯蒂回归
' S m0 ]2 M3 _' F8 COrdinal variable, 有序变量
/ Y/ d% v9 e! {$ u6 G3 ]7 u rOrthogonal basis, 正交基7 U% p# `6 { q+ ]6 Q
Orthogonal design, 正交试验设计
. V' ]+ x" Y" JOrthogonality conditions, 正交条件
: c+ N+ i U/ d" JORTHOPLAN, 正交设计 ( \; {7 F! b2 i' N- h
Outlier cutoffs, 离群值截断点
3 a, C0 s7 b7 P3 H5 b" n8 `Outliers, 极端值
K4 y6 p! C R* pOVERALS , 多组变量的非线性正规相关
( i/ q8 K# q1 x- `6 \) [0 R v6 uOvershoot, 迭代过度
+ ~1 B0 \# L0 A# H0 j& s; ]Paired design, 配对设计
# a8 j, F, h: p: D! z' \; m" lPaired sample, 配对样本+ H; ]0 J4 U7 m3 c$ w
Pairwise slopes, 成对斜率# E1 n2 }4 m" d5 c" K! G8 w& f/ ]
Parabola, 抛物线# X% M2 v! n. U+ a" Y: N1 o# R4 H
Parallel tests, 平行试验# y' d! Q) {8 X7 ^3 D6 P: Z" k
Parameter, 参数$ ], ~5 a3 \/ a* J% `: K+ Q
Parametric statistics, 参数统计; w* c3 S1 t# Y9 ~! w
Parametric test, 参数检验/ i9 x9 s# t% w' r0 S% w0 @
Partial correlation, 偏相关
7 T" e" d' o! i5 ]; U F8 wPartial regression, 偏回归2 x; }) M/ b5 e/ t
Partial sorting, 偏排序
7 ?; b. y7 b9 D/ gPartials residuals, 偏残差1 t4 U7 W+ i$ A4 ^8 v' d
Pattern, 模式
( d+ I. T% W* PPearson curves, 皮尔逊曲线. W& H- a3 X* w: @, O
Peeling, 退层0 B! u7 d) P+ s8 x- [+ e* k
Percent bar graph, 百分条形图
% T3 A2 ]+ L/ A" u: UPercentage, 百分比
2 u+ Q5 M) X9 b. GPercentile, 百分位数
& R2 v$ A% N: APercentile curves, 百分位曲线( `' g+ p( |- ?6 N. V
Periodicity, 周期性& C; x% k5 A, A D3 `# _
Permutation, 排列
# b8 T4 Z/ ^* F5 H8 lP-estimator, P估计量( T. N& S. h1 N3 J: `% G' [# ]+ Z5 l0 `
Pie graph, 饼图2 b. f. N3 z' O! c* T
Pitman estimator, 皮特曼估计量" |9 j) P) y4 ~' ^. ~
Pivot, 枢轴量
" ~6 E" _/ v, z& T. D* hPlanar, 平坦
3 l9 N3 `' m L, c& [5 SPlanar assumption, 平面的假设
* R6 V8 K* L( q6 o/ ?7 ^PLANCARDS, 生成试验的计划卡9 F+ j# `) n5 Z$ {7 E; E
Point estimation, 点估计
: _: K8 J. @6 LPoisson distribution, 泊松分布. B [7 X' Y" q$ v8 ?
Polishing, 平滑6 i) z" e& \( l/ ?2 k
Polled standard deviation, 合并标准差) }9 A8 Q- J2 Q/ }
Polled variance, 合并方差5 m5 b, x. O% h" F: r6 _) Z
Polygon, 多边图
4 w. ^# d2 b* ]# ` b% @Polynomial, 多项式$ K$ E# f/ Q5 P+ Y0 z
Polynomial curve, 多项式曲线- d8 E. N! M4 z/ Q+ W$ o2 G5 P6 o, S
Population, 总体
9 H y$ e5 z; ^( \ ZPopulation attributable risk, 人群归因危险度' b1 T" Z+ b0 G" c9 V
Positive correlation, 正相关$ t. \" h$ c4 p& _2 L
Positively skewed, 正偏
+ Q0 P% E4 Q0 K9 d1 ?$ i! W3 KPosterior distribution, 后验分布
% E. s8 V: W: r1 r) j VPower of a test, 检验效能
2 h, g3 A% s% W0 [6 `1 E. fPrecision, 精密度4 F6 M+ a, b+ O) ?
Predicted value, 预测值
+ {: s7 {6 o/ T9 H' }& \: U. N, nPreliminary analysis, 预备性分析& t1 h$ B* P# b- z! R# y* {
Principal component analysis, 主成分分析 g& I, \+ b; u# h: a; x
Prior distribution, 先验分布3 [2 W9 v5 R0 o; X1 o7 c6 N
Prior probability, 先验概率
4 l4 A8 s* l% D; r$ ?+ i t* sProbabilistic model, 概率模型' y2 p$ N# ] H4 D3 [$ w
probability, 概率
# w) O$ S: s/ w1 JProbability density, 概率密度3 G6 D6 H2 y: K8 Q) h J( W1 i
Product moment, 乘积矩/协方差
. p8 X, @( A( M m9 r' M3 C! yProfile trace, 截面迹图0 j9 B9 ?: ]/ u X
Proportion, 比/构成比
& `; ^* `0 T8 X( @6 BProportion allocation in stratified random sampling, 按比例分层随机抽样
& [" k( W; j, H' u& r7 QProportionate, 成比例
4 Y* S/ T" ^8 ]Proportionate sub-class numbers, 成比例次级组含量+ `; h+ c/ n; G E' `3 T
Prospective study, 前瞻性调查
' \$ z5 p8 k6 J8 ^; BProximities, 亲近性
9 h2 I! Q3 D8 [5 _2 E2 M5 ]Pseudo F test, 近似F检验
" ~0 k/ j$ W- S, xPseudo model, 近似模型
3 C* m( I u9 Q TPseudosigma, 伪标准差9 c% B m/ K" l9 ~+ y4 P" n+ r+ H* `
Purposive sampling, 有目的抽样* U6 R4 P: O3 g5 p2 G
QR decomposition, QR分解
# P7 K+ W- y" ^ W! \1 K, fQuadratic approximation, 二次近似: O4 i- {9 c7 D6 s% b
Qualitative classification, 属性分类 [" P8 Z' m! C
Qualitative method, 定性方法
; W( O/ x Z6 K! QQuantile-quantile plot, 分位数-分位数图/Q-Q图
" E7 f, g1 ?# h& oQuantitative analysis, 定量分析
3 U" v/ O5 k5 bQuartile, 四分位数
( G8 n! S a x. D. J8 `+ P( uQuick Cluster, 快速聚类7 w U4 ]$ J4 Q1 k) G- l6 Y
Radix sort, 基数排序
% h' z+ n2 V8 n1 IRandom allocation, 随机化分组" a2 E7 R! g7 r3 B: V
Random blocks design, 随机区组设计; M& ^4 |' _0 {: S6 ~
Random event, 随机事件0 {$ n+ p2 U( ~. \) o X/ E9 V4 \
Randomization, 随机化5 k, X" ^, M G5 K X0 W
Range, 极差/全距
* S1 X7 G2 T* F8 c0 ~* a9 ~# tRank correlation, 等级相关2 _7 V8 Q) O- \9 c- ~- x' [2 \
Rank sum test, 秩和检验
- @7 A+ N- H+ uRank test, 秩检验
, l* J7 y0 L7 `/ f4 S7 P/ [2 mRanked data, 等级资料
! x/ C; e: t/ @% |/ URate, 比率
4 s! {0 r# Z4 R JRatio, 比例: ?8 E. s7 B- X( I3 F5 Z4 T v. d
Raw data, 原始资料
' Q) C5 k, p8 aRaw residual, 原始残差
X5 x( N% A9 c8 i* zRayleigh's test, 雷氏检验
7 T: o- H# m, T: SRayleigh's Z, 雷氏Z值
/ ]' B k0 _' Z1 C7 m; v* JReciprocal, 倒数( p5 ^6 g$ z/ T6 h) X5 J
Reciprocal transformation, 倒数变换# p1 H4 e: j" n/ J
Recording, 记录
& a4 F) t9 L* j( L M; ]Redescending estimators, 回降估计量
9 D2 A* y7 p& B- f: W" {/ \Reducing dimensions, 降维
3 N# t5 Z, y/ @# ~Re-expression, 重新表达% t ?, E b3 z; {1 ]7 E; b
Reference set, 标准组6 [" W' E! J- \/ Z
Region of acceptance, 接受域- U6 l" A+ z: o6 I2 o
Regression coefficient, 回归系数+ p' F% B" ^* G5 Z9 m- X$ q
Regression sum of square, 回归平方和
: s) S% t4 n; }" dRejection point, 拒绝点
% ~- i/ V" e; G( ORelative dispersion, 相对离散度0 H* o A- f v. |7 J5 f
Relative number, 相对数
, |! ]8 z, R% ^Reliability, 可靠性
F! S( I, o& X0 PReparametrization, 重新设置参数
. \8 G# I8 b) r7 j, @Replication, 重复
* R" |) O9 G" c& h1 _Report Summaries, 报告摘要
/ w) @2 n$ J/ L1 i: b! G: \Residual sum of square, 剩余平方和
/ n* J) m2 h/ i s4 O- aResistance, 耐抗性: a2 x; ~: m' k" H% D
Resistant line, 耐抗线
5 k. [( i( w( c$ C1 Y1 gResistant technique, 耐抗技术
& s& s/ U, A' P8 o9 G+ u. lR-estimator of location, 位置R估计量! n# s0 B- W `# i9 ^
R-estimator of scale, 尺度R估计量
, Q* ?. a% M4 w; J( P9 }: B( G2 wRetrospective study, 回顾性调查/ J3 W# A/ f$ @5 Q
Ridge trace, 岭迹
2 g0 B+ M V: @1 e3 o( `Ridit analysis, Ridit分析1 R) b1 O! d+ D, u2 ^8 y. m
Rotation, 旋转
8 T& y7 i$ Z0 u+ ]/ U+ jRounding, 舍入* N$ X$ g) X! B3 c: u" i) a; d
Row, 行8 G! J" h5 I- u" A& ]1 X4 s
Row effects, 行效应+ [7 c' k( ]' |: N( Z
Row factor, 行因素2 P- F3 d1 @& m5 X/ l1 o4 N; z# h: ^' L
RXC table, RXC表
8 l1 F. v% X |! _- RSample, 样本
/ W+ |$ m6 d2 H# \) N0 [5 sSample regression coefficient, 样本回归系数
1 X! }7 B/ }' \$ `Sample size, 样本量3 _' g6 `- [2 C _+ x: G2 m/ I- x' I* J
Sample standard deviation, 样本标准差
% ^$ ^# J; o9 jSampling error, 抽样误差
6 @& E. p. \0 o$ VSAS(Statistical analysis system ), SAS统计软件包
. e+ |3 A8 X2 c, b( C2 `+ \+ kScale, 尺度/量表
! Z' J: h& |' K( y' N, i3 {5 iScatter diagram, 散点图% W( N% q3 z* t1 J2 y+ E( h! U
Schematic plot, 示意图/简图% P/ Y8 w) Y( Z$ `
Score test, 计分检验0 e7 Q: q% x; a4 A; x
Screening, 筛检: x( ?& f/ Q& o. h; D# h
SEASON, 季节分析
6 @+ b5 I' X( C% b; v: P5 YSecond derivative, 二阶导数' `7 j. A5 N) }9 b3 \/ S
Second principal component, 第二主成分
& o: b z1 M' m' ]SEM (Structural equation modeling), 结构化方程模型 ) a; j0 M% v) O. |9 ] I1 ]
Semi-logarithmic graph, 半对数图' i( I1 @0 ~7 t% `# H! w
Semi-logarithmic paper, 半对数格纸
% U" u0 n& M4 o3 RSensitivity curve, 敏感度曲线) [' X- {+ C$ |5 M7 ^8 m1 P
Sequential analysis, 贯序分析
- w' y+ P- l4 E& P& O' Q/ {, fSequential data set, 顺序数据集
$ v! K6 G! u1 i5 n- W ^, t" ESequential design, 贯序设计9 O: @* i( Y2 M" F! N$ j1 k
Sequential method, 贯序法8 v2 q9 V0 ~4 O" b
Sequential test, 贯序检验法" C& w6 `8 H$ }: g% A
Serial tests, 系列试验: z% Q6 B9 O" I5 M: b+ y
Short-cut method, 简捷法
; B" }4 S# a2 r& z9 _Sigmoid curve, S形曲线
! x5 E0 y' q% e) b% ~" P& gSign function, 正负号函数/ h0 d% a/ K! m# p
Sign test, 符号检验+ O6 \2 Z& @7 N$ q8 n2 F3 ~$ N
Signed rank, 符号秩) g) g' F0 @: t4 _
Significance test, 显著性检验9 l- k( w. @ r. G* ~$ }9 L* N
Significant figure, 有效数字; L6 Z& K/ m0 b/ N7 ?& {2 Z. {
Simple cluster sampling, 简单整群抽样
8 s2 U" X4 v4 ^7 ?1 sSimple correlation, 简单相关& Z& P9 {+ U" e7 v
Simple random sampling, 简单随机抽样
- C% R4 N9 S- x) s) sSimple regression, 简单回归
+ ?" @: V" m4 n* ^simple table, 简单表
, x6 E8 ~' h, U% n( \Sine estimator, 正弦估计量6 o/ R! P/ D9 I5 q3 Z3 m
Single-valued estimate, 单值估计
. z) R5 P& `: \Singular matrix, 奇异矩阵. q4 v3 h% k. G O
Skewed distribution, 偏斜分布: ?8 m! r" l; ]" j! M% S' ]
Skewness, 偏度* D* T0 w/ [: b+ Y$ N
Slash distribution, 斜线分布; b) N, C, c" w( _
Slope, 斜率
2 p* F; @5 b8 z- c3 ]) i7 tSmirnov test, 斯米尔诺夫检验% f! w* Y, q! E- M
Source of variation, 变异来源
1 u& J5 \7 c/ z& C% mSpearman rank correlation, 斯皮尔曼等级相关) N6 c% w8 I; O
Specific factor, 特殊因子
" K1 b/ U. F& U& XSpecific factor variance, 特殊因子方差& Z# g5 Y0 w6 C5 g+ {- P: W' h, o( h
Spectra , 频谱
5 y' b: {: @. x/ X, ESpherical distribution, 球型正态分布$ ~6 G: e. M8 b) h" j
Spread, 展布3 w7 S" u9 I) N7 h: i
SPSS(Statistical package for the social science), SPSS统计软件包! A" U2 w4 Q/ [4 ^; V0 J
Spurious correlation, 假性相关
: G* Y% g, B# ^! P4 F0 W mSquare root transformation, 平方根变换) H8 b! S$ V2 F) i+ O
Stabilizing variance, 稳定方差
/ |. N1 O. n m; U3 t/ LStandard deviation, 标准差5 V y; a: h# w7 ]* f. ?3 n6 P
Standard error, 标准误
, I/ d; J0 Z# o: q6 x; f5 e; BStandard error of difference, 差别的标准误
. w0 R& f) b' k' k6 }* [) e/ EStandard error of estimate, 标准估计误差
/ h6 D" u! a& S/ e0 gStandard error of rate, 率的标准误
2 w/ D6 ^/ I: ]. W1 ~5 ~! mStandard normal distribution, 标准正态分布3 ~* {6 B( W5 A1 w
Standardization, 标准化
- p( S& q) t ?& A/ A2 }1 ]& cStarting value, 起始值
" k' a- Z$ |; y: RStatistic, 统计量
6 m3 [" ?. ?' ]2 ]$ YStatistical control, 统计控制8 t) H7 ~3 ?( `- V/ ]5 `
Statistical graph, 统计图
4 M; t2 e# h6 d) f! m6 S7 KStatistical inference, 统计推断
; h! j2 E# r1 ?% v" b CStatistical table, 统计表
2 Z( s; e+ C6 V# ZSteepest descent, 最速下降法
0 _- p6 Q9 g% lStem and leaf display, 茎叶图
2 X" j: W9 c% E) t" u. L& BStep factor, 步长因子
0 K F) R2 o8 x6 C k9 b1 q3 y4 pStepwise regression, 逐步回归
: E1 c% g# L2 s! n8 f p5 T& |Storage, 存
/ _( l" c0 f- {% W3 b5 LStrata, 层（复数）
G! M0 k8 D/ |( \Stratified sampling, 分层抽样
% k- m" V7 |0 g8 m/ j8 j7 w8 tStratified sampling, 分层抽样
1 i0 p f3 [* _Strength, 强度
: `$ w& i& v( k: oStringency, 严密性
6 Q5 W. \, Z( ?. }% }6 ^Structural relationship, 结构关系
6 ~( t/ L3 C2 \Studentized residual, 学生化残差/t化残差
" @- w. `% w; x# @2 o, `. z% jSub-class numbers, 次级组含量
7 m1 o k" `* | ?" eSubdividing, 分割
1 h" s5 G% I* y3 X7 B' cSufficient statistic, 充分统计量3 d' c) F6 ^# r- d- O7 P% a* ]
Sum of products, 积和
! s& C c' B8 f* k4 w# }Sum of squares, 离差平方和% ~2 E P+ J& A8 @3 Y1 Z. I4 T" k
Sum of squares about regression, 回归平方和
& z* ^0 _; ?! `! OSum of squares between groups, 组间平方和
R8 P0 z. u# i( L' v$ qSum of squares of partial regression, 偏回归平方和
* A# J7 _' b' d; K& bSure event, 必然事件* L% E7 y# `' O+ |0 R
Survey, 调查6 y' J5 `3 |0 f2 j; B' X U7 |6 r
Survival, 生存分析" p- N5 m. R6 h* _
Survival rate, 生存率
- d4 X( R# Q; G6 l, h8 MSuspended root gram, 悬吊根图
& V3 _' d# d) N0 S$ USymmetry, 对称
( S5 s2 U; A3 p, {+ W0 @Systematic error, 系统误差
& z% n3 F: o; [) H2 dSystematic sampling, 系统抽样
_, _) `% l2 f4 N5 DTags, 标签/ T) k. F% ~/ s% o1 r, ?9 ~/ J
Tail area, 尾部面积8 s6 k Z0 j/ x, u# p
Tail length, 尾长! O! y' l4 i4 L- x) o4 f+ K2 h
Tail weight, 尾重! h9 x/ x7 M* s
Tangent line, 切线
& l' { f% w, y0 T" V+ B1 DTarget distribution, 目标分布
+ O% ^) h8 a, C4 j7 u5 MTaylor series, 泰勒级数
' }! T8 l! s3 z2 B4 GTendency of dispersion, 离散趋势
0 B8 m$ u' L+ H! \9 Z% B, Y! ATesting of hypotheses, 假设检验, u! Q8 c+ Z+ ^
Theoretical frequency, 理论频数2 k% ]" ?/ t. P0 l4 m
Time series, 时间序列
: x5 i e( s. Y- {. p9 g, [( ?Tolerance interval, 容忍区间
% e/ A( ?0 N$ VTolerance lower limit, 容忍下限
2 Y7 w% J+ J" v. ` L3 KTolerance upper limit, 容忍上限* s6 x8 d5 {" G: W' Y4 I
Torsion, 扰率9 _6 i: S7 v7 U j; n
Total sum of square, 总平方和
3 ?& N B3 v: J) ]9 }Total variation, 总变异
6 ~% t" f7 s* E0 \8 {, o( O. u; e1 nTransformation, 转换
, P! _$ C, y8 V( ?" yTreatment, 处理
0 ^. ~) u: r A. C$ V2 RTrend, 趋势
' M* o D6 y- G, [2 C2 PTrend of percentage, 百分比趋势5 F# t3 d# k% _3 m% w/ [" v! Y
Trial, 试验
6 O2 X4 K6 v3 [; hTrial and error method, 试错法
# O( H/ j) D; [4 ~Tuning constant, 细调常数$ A# {# s. A6 ?. z( c. j
Two sided test, 双向检验
4 w4 `6 z; X0 w2 vTwo-stage least squares, 二阶最小平方
) q! m' \4 i1 ?5 b! QTwo-stage sampling, 二阶段抽样
* c7 S$ b- e) K4 x n O$ ZTwo-tailed test, 双侧检验8 [! {( F$ A) g/ k3 N& H( T& M
Two-way analysis of variance, 双因素方差分析
" k# ^5 v2 M: r( ^Two-way table, 双向表
; }1 b6 Z. R a6 {+ eType I error, 一类错误/α错误' q, H: I& ]; E2 r! {5 Q
Type II error, 二类错误/β错误
: {$ D6 \$ S: j+ e2 JUMVU, 方差一致最小无偏估计简称: ~# Y5 ?, Z3 ?0 m! d- J
Unbiased estimate, 无偏估计3 R) E- ?+ S) d' S9 S
Unconstrained nonlinear regression , 无约束非线性回归# k1 q" a+ p9 p' |3 e: z" a
Unequal subclass number, 不等次级组含量
9 E/ v( z+ m% @; ?' ~Ungrouped data, 不分组资料
7 B4 R7 V0 V. c. i" GUniform coordinate, 均匀坐标
1 G( m2 B* x0 |! `/ K1 p" lUniform distribution, 均匀分布4 @5 Z: c7 E4 I1 o
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计4 J f. g+ i% X! U
Unit, 单元
5 f7 w/ B4 e' g6 RUnordered categories, 无序分类
+ x" E) z. `8 S. RUpper limit, 上限5 d! R/ c- H9 Z) ]* K/ d7 U
Upward rank, 升秩$ d- h4 q) m# T" |4 g
Vague concept, 模糊概念& Z/ T3 I u2 Y
Validity, 有效性$ M- i9 j. K* s
VARCOMP (Variance component estimation), 方差元素估计+ [" h6 i- a) n s5 g7 W9 ?
Variability, 变异性
" ]" p8 A- N6 x2 N5 wVariable, 变量
* y1 \% |* V9 W, o# Q( K" N" ?) c. MVariance, 方差. \/ P0 S0 Y0 Q
Variation, 变异
b' k1 R: T3 l. ~1 l3 `Varimax orthogonal rotation, 方差最大正交旋转) A9 M- B! y1 Y* f3 D( h
Volume of distribution, 容积, Q6 q( V$ ]" d1 V' Y* ]! _5 M) Y
W test, W检验
- N' \; H# e2 t [. _9 GWeibull distribution, 威布尔分布1 X9 Y8 c; ], O. Y! ?9 O
Weight, 权数
# K! z. q: R& H% D h) uWeighted Chi-square test, 加权卡方检验/Cochran检验
% E6 J5 o3 z9 U' N2 _Weighted linear regression method, 加权直线回归
$ z- A- S6 E& l9 tWeighted mean, 加权平均数
4 @: f" x( R) tWeighted mean square, 加权平均方差
) a; b/ [! x" ?: v4 Y- ZWeighted sum of square, 加权平方和! t0 B# k+ F9 r2 l' ]
Weighting coefficient, 权重系数8 ^& ?+ R- I0 \7 z% L
Weighting method, 加权法
; `2 X. v3 [" M6 }, Z1 GW-estimation, W估计量
( @, {* t* _+ E" _5 s( ^$ O# T- rW-estimation of location, 位置W估计量
. {- G6 `$ J* B( X6 T" }2 M7 b& U5 IWidth, 宽度% Y5 C+ Z* L* P5 N4 A
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验, T5 I+ F+ u7 M+ q! M1 y5 M* r+ ~( r+ q
Wild point, 野点/狂点" N1 i5 Z0 T6 O& [6 e; G
Wild value, 野值/狂值
3 k# y. \/ k5 [4 SWinsorized mean, 缩尾均值& I) P; i/ m9 [ j3 z
Withdraw, 失访 4 @) _) W% B, G
Youden's index, 尤登指数0 s2 N0 o# X7 M7 Y: k% m$ T" K' v
Z test, Z检验
/ V) q# O0 K/ [1 ]: s( P1 xZero correlation, 零相关. ~ G7 Q. j7 O
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
